Meta-analysis of the psychometric properties of the Pain ...

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Meta-analysis of the psychometric properties of the Pain Catastrophizing Scale and

associations with participant characteristics

Claire H B Wheeler1, Amanda C de C Williams2, Stephen J Morley1†

1 Leeds Institute of Health Sciences, Level 10, Worsley Building, Clarendon Way,

Leeds, LS2 9NL, UK

2 University College London, London WC1E 6BT, UK

† died April 2017

Pages: 23

Number of figures: 3 [2 in text; 1 supplementary]

Number of tables: 6 [4 in text; 2 supplementary]

Corresponding author: Claire Wheeler

Mailing address:

Programme in Clinical Psychology, Leeds Institute of Health Sciences

Level 10, Worsley Building

Clarendon Way

Leeds, LS2 9NL, UK

Email: [email protected]

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Abstract

The aims of this study were to review the psychometric properties of the widely used Pain

Catastrophizing Scale (PCS) using meta-analytic methods, and to investigate the relationship

between PCS scores and participant characteristics. A systematic search from 1995 found

229 experimental, quasi-experimental and correlational studies that report PCS scores.

Multivariate regression explored variables related to pain catastrophizing and participant

demographics. Across studies, good internal reliability (α = 0.92, 95% CI 0.91 - 0.93) and

test-retest reliability scores (Spearman ρ = 0.88, 95% CI 0.83 - 0.93) were found for PCS

total scores but not for subscales. PCS scores were unrelated to age or gender, but strongly

related to participants’ pain type, highest in those with generalized pain. Language of the

PCS also affected PCS scores, with further research necessary to determine linguistic,

cultural or methodological (e.g. sampling strategy) influences. Study type influenced PCS

scores with non-randomized controlled trials reporting higher PCS scores than other study

types, but results were confounded with pain diagnosis, as controlled trials were more likely

than quasi-experimental studies to recruit clinical samples. The meta-analytic results provide

insight into demographic influences on pain catastrophizing scores and highlight areas for

further research. The advantages of systematic review and meta-analytic methods to achieve

greater understanding and precision of psychometric properties – in this case, of the PCS –

are applicable to other widely used outcome tools.

Keywords

Outcome measure; PROMS; Systematic review; Reliability

1 Introduction

1.1 Pain catastrophizing

Pain catastrophizing is one of a number of concepts describing the psychological experience

of pain. Beck first described catastrophizing in general as a cognitive error, or ‘an

irrationally negative forecast of future events’ [20] (p.745). Pain catastrophizing is the

forecast of future pain and a person’s inability to divert attention away from the pain [13];

also described by Sullivan and colleagues as ‘an exaggerated negative mental set brought to

bear during actual or anticipated painful experience’ [25] (p.53).

1.2 Established psychometric properties of the PCS

The Pain Catastrophizing Scale (PCS) is widely used as the ‘reference standard

psychometric tool for pain catastrophizing’ [13]. Respondents are asked to rate 13 pain-

related statements on a 5-point Likert scale. During its development, Sullivan and colleagues

investigated the factor structure in a sample of 439 students [23]. Principal components

analysis established that the PCS assessed three related dimensions of magnification

(evaluation of the pain as a threat), rumination (repeated worry) and helplessness (belief that

nothing can help to resolve the pain). Confirmatory factor analysis has since been used in

English and Dutch versions to confirm this three-factor structure compared to a

unidimensional or two-factor structure in students [18], community and pain outpatient

samples [17], and pain-free students, chronic low back pain patients, and fibromyalgia

patients [28]. Overall, these studies demonstrate consistency of the three-factor model of

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pain catastrophizing across participant groups in English and Dutch versions of the

questionnaire.

Existing data on the reliability of the PCS reports adequate to excellent internal validity

scores (coefficient alphas: total PCS = 0.87 - 0.93, rumination = 0.87- 0.91 magnification =

0.66 - 0.75, and helplessness = 0.78 - 0.87; [18; 23]). Pedler reported in a commentary

review that ‘there are currently little data available regarding the test-retest reliability,

sensitivity to change, and clinically meaningful change of the PCS’ and that ‘[f]urther

research investigating these dimensions of the PCS would significantly increase the clinical

utility of this tool’ [19] (p.137). More broadly, there are concerns that many self-report

measures used in health care, including pain, tend to be developed and used in an ad hoc

way, without thorough validation and reliability testing across wide samples of participants

[15] (p.34).

1. 3 Pain catastrophizing scores and personal characteristics

Studies have been conducted to explore potential differences in pain catastrophizing between

people of different ages, genders, from different cultural backgrounds, and with different

pain diagnoses. Such information helps to explain the extent to which the construct of pain

catastrophizing can be viewed as stable across populations. Women tend to score higher than

men [4; 12; 23; 26; 27], although one study reported no sex difference [22]. Older adults

tend to score lower than younger adults [11; 24] but the effect is reversed in adolescents,

where older adolescents score higher than younger [1]. Although a number of studies have

reported pain catastrophizing scores for participants with different pain diagnoses (including

many studies in this review), no review or commentary has compared or combined these.

There have been no studies of the difference in pain catastrophizing scores of participants

using different language versions of the PCS or other measures of pain catastrophizing. Any

disparity in PCS scores of participants using different language versions could be due to

translations of the outcome measure or to cultural differences in the experience and

expression of pain catastrophizing. Existing studies report higher levels of pain

catastrophizing in Chinese Canadians compared to European Canadians [9] and in African-

Americans compared to white Americans [4] using the same language scale. Therefore some

limited evidence from healthy participants suggests the presence of cultural factors in

mediating pain catastrophizing scores.

The rather inconsistent findings from studies on specific participant groups leave open the

question of whether there are systematic age, sex, or other demographic differences in pain

catastrophizing; no comprehensive investigation of such differences in pain catastrophizing

has been attempted.

1.4 Aims of this review

The aims of this review were to systematically obtain data on PCS scores from a wide range

of studies and first to explore the psychometric properties of the PCS using meta-analytic

methods, then to investigate whether there were any clear differences in PCS scores

according to personal characteristics of participants. The review also served to test the use of

meta-analysis to investigate psychometric properties of self-report instruments widely used

in psychological treatment.

1. Methods

1.1 Protocol and registration

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The research protocol for the review and meta-analysis was registered on PROSPERO

(prospective register of systematic reviews) at the University of York’s Centre for Reviews

and Dissemination (CRD), registration number CRD42016032863.

1.2 Eligibility criteria

English language studies reporting baseline PCS scores (those collected before any

intervention) were included in the meta-analysis. Participants in those studies had to be aged

18 or over, could have any health condition or none, and both randomized and non-

randomized studies were included. Included studies were those that reported demographic

and clinical information about participants (age, sex, diagnostic category) and psychometric

data for PCS scores (mean, standard deviation, sample size).

1.3 Search strategy

The search strategy was adapted for Cochrane Library, Cinahl, Embase, PsycInfo, PubMed,

and Web of Science (all 1995-present) by using wildcards and terms relevant to each

database (an example search strategy is included in Suppl. Fig. 1). The last search was run

on 30 November 2015. Requests were sent to authors for data missing from otherwise

relevant studies, resulting in eight responses with eligible scores to 81 requests for missing

PCS data; and no eligible scores for 21 requests sent for missing demographic data.

1.4 Study selection and data collection

One reviewer (CW) screened the title and abstract of the studies retrieved in the database

searches. A random sample (using a random number sequence generator) of 5% of the

papers were screened by title and abstract by a second reviewer (SM) and the inter-rater

reliability calculated. Discrepancies were discussed and resolved. The data collection form

was adjusted following the pilot to allow for pooled data from studies that reported only PCS

subscores, or scores from subgroups but personal data from the whole sample. Data items

extracted from data including participant characteristics, study data, and study type are

presented in Suppl. Table 1.

1.5 Risk of bias in individual studies

A component approach was used to assess the risk of bias in each included study [14].

Relevant components from the Quality Assessment Tool for Observational Cohort and

Cross-Sectional Studies [16] were used in this review and meta-analysis:

1. Was the study population clearly specified and defined?

2. Was the participation rate of eligible persons at least 50%?

3. Were all the subjects selected or recruited from the same or similar populations

(including the same time period)? Were inclusion and exclusion criteria for being in the

study pre-specified and applied uniformly to all participants?

Sensitivity analysis was conducted to ascertain the impact of bias from the above

components on the overall effect sizes found in the meta-analysis. Meta-analysis of effect

size was conducted first for all studies, and then repeated only for studies known to be

eligible (meeting all three risk of bias criteria), following the Cochrane method [7]. There

was unlikely to be a high risk of publication bias in the included data, so no risk of bias

analysis across studies was undertaken.

1.6 Meta-analysis to explore the psychometric properties of the PCS

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2.6.1 Calculating weighted means, standard deviations and reliability alphas of PCS scores

Weighted scores were computed for the PCS mean, standard deviation, and Cronbach’s

alpha for each sample in which these data were available. Weights were based on the

standard error for each sample. The weighted scores were used to compute the mean,

standard deviation, reliability coefficient, confidence intervals, and random effects variance

components for PCS scores across studies.

2.6.2 Reliability estimates

The internal consistency reliability for the PCS and its subscales was calculated by finding

the weighted mean of the Cronbach’s alpha statistics reported in studies using the PCS. The

test-retest reliability for the total PCS scale was calculated using the weighted mean test-

retest reliabilities reported in studies.

2.6.3 Subgroup analysis

Wilson’s macros for SPSS [29] were used to conduct Hedges-Olkin random effects meta-

analysis [5] on participants grouped by pain diagnosis. Hedges and Olkin’s method of meta-

regression was chosen for this analysis because of its coherence with the theory of data used

throughout: that including all available data and accounting for bias through weighting

provides a more comprehensive analysis than excluding data. Hedges and Olkin’s method

uses a pooled variance estimate to standardize the difference between group means. Biases

were corrected based on a sample size statistic using weighted scores.

A Q statistic was calculated to obtain a test of the homogeneity of the effect size (the extent

to which individual effect sizes vary around the mean effect size); it is the standardized sum

of squared differences between each effect size and the mean effect size:

𝑄 =∑(𝑑𝑖 − 𝑑+)

2

�̂�𝑑𝑖2

𝑘

𝑖=1

where k is the number of studies or samples included, d+ is the mean effect size, and

σ2d is the weighted average based on the variance of the unbiased effect sizes

2.6.4 Exploration of the heterogeneity of the mean PCS score across studies

The I2 measure of heterogeneity was calculated for the grand mean PCS score and for the

mean PCS score of diagnostic subgroups. It was necessary to transform the Q value reported

in the original meta-analysis to an I2 value owing to Q having ‘too much power as a test of

heterogeneity if the number of studies is large’ [7] (9.5.2).

The I2 value was calculated from Q as follows:

Ι2 =(𝑄 − 𝑑𝑓)

𝑄

I2 is reported as a percentage, where over 75% indicates substantial heterogeneity between

trials [8].

2.6.5 Use of multiple regression to explore heterogeneity of PCS scores

SPSS version 23 [10] was used to conduct random-effects meta-analysis and meta-

regressions. Multivariate meta-regression was conducted to explore the heterogeneity of

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mean PCS scores across participant groups by testing their association with variables and

other study features.

Wilson’s macro for SPSS was used to employ Hedges and Olkin’s psychometric meta-

analysis method, with results transformed from Fisher’s z scores back to r scores after the

analysis. This method of meta-regression uses a weighted least squares (WLS) procedure

and scores from each study that are weighted by the inverse of the study’s sampling error

bias. Variables entered into the first meta-regression were: pain category (type of pain

diagnosis), mean age of participants, proportion of female participants, year of study (studies

were categorized into ranges of three years), study type, and language of PCS used. A

further meta-regression was then run using pain category as the only variable. Re-running

the meta-regression with this clinically relevant variable meant that more studies were

included, because some studies were excluded on the grounds of missing data — including

those with no data on the gender of participants — in the first meta-regression.

2. Results

3.1 Study selection

220 studies were identified for inclusion in the review and meta-analysis (see Fig. 1 for

searching and screening process). Suppl. Table 2 provides details of reasons for the

exclusion of studies.

[Insert Fig. 1 here] Flow diagram showing the searching and screening stages of papers to be

included in the review and meta-analysis.

Inter-rater reliability was calculated for the screening of papers that was completed by the

two independent raters (CW and SM). There was 90.3% agreement, with a Cohen’s kappa of

0.87 (accounting for agreement due to chance), meeting criteria for reliable inter-rater

agreement [3] (p.56). Discrepancies were discussed and resolved between the raters, with a

conservative approach followed in order to allow for further screening at a later stage.

3.2 Data cleaning and preparation

Data cleaning was conducted to remove double-counted data and data with errors (two

papers in total). Seven further papers contained surprisingly low PCS scores but no evidence

of the source of error; these papers were not removed from the analysis. Instead, meta-

analytic methods were applied to correct for artifacts and error.

3.3 Study characteristics

Data from 220 studies published between 1997 and 2015 was included in the initial analyses.

Included studies were cross sectional, psychometric, case series, randomized controlled and

non-randomized controlled trials, case controlled, and cohort studies. Sample sizes ranged

from 3 to 1,786, and many studies reported PCS scores and related data for two or more

groups of participants so data were collected for 329 groups altogether. The PCS was

represented by 21 languages translated from English.

Mean ages of participants in studies ranged from 19 to 76, with a grand mean age of 45

years, sd = 12 (for both weighted by sample size and unweighted). The grand total number

of participants across included studies was 42,976. The gender ratio was 55:32:13 for male,

female, and participants whose gender was not reported.

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Mean PCS scores across all participant groups ranged from 3.2 to 43.8, with a grand

weighted mean of 20.22 using a random effects model (weighted SD = 10.26, 95% CIs of

mean = 19.30 - 21.14). Unless otherwise stated, ‘PCS score’ refers to the total scale score.

Subscale scores are reported where available. Results of individual studies are presented in

Suppl. Table 1 due to the large number of studies (220) and larger number of participant

groups in the studies (k = 339).

3.4 Risk of bias analysis

Three screening questions were used to assess the risk of bias within studies:

Q1 = Was the study population clearly specified and defined?

Q2 = Was the participation rate of eligible persons at least 50%?

Q3 = Were all the subjects selected or recruited from the same or similar populations

(including the same time period)? Were inclusion and exclusion criteria for being in

the study pre-specified and applied uniformly to all participants?

70 studies fulfilled criteria for all three screening questions. The weighted PCS scores for all

studies included in the review and for just those studies meeting all the risk of bias criteria

were calculated. Subgroup analysis determined the difference in PCS scores between studies

that did and did not meet all of the risk of bias criteria; results are presented in Table 1.

[Insert Table 1 here]

Regression analysis showed the PCS score to be significantly related to whether or not a

study met all risk of bias criteria, B = 16.64, SE = 0.49, 95% CI = 15.68 - 16.60, p < 0.001.

Analysis of variance showed a significant correlation between the type of study conducted

and whether or not the study met all risk of bias criteria, B = 5.62, SE = 0.12, 95% CI =

5.38-5.85, p < .05.

3.5 Meta-analysis to explore the psychometric properties of the PCS

3.5.1 Heterogeneity of the grand mean PCS score

The I2 value of the grand mean PCS score is 98.96%, representing very substantial

heterogeneity between studies. The high I2 value might also suggest that the overall mean ES

is misleading because there are subpopulations of studies represented that have different ES

values; this supports the need to conduct subgroup analysis to further determine the origins

of heterogeneity of mean PCS scores across participant groups (see section 3.5.4).

3.5.2 Reliability

Estimates of the internal consistency of the PCS full scale and subscales were based on

Cronbach’s coefficient alpha[2]. After weighting and averaging reports from 40 studies, the

full scale alpha = 0.92 (95% CI 0.91 - 0.93). PCS subscale data was reported in 21 studies,

with average internal consistency of alpha = 0.89 (95% CI = 0.87 - 0.91) for the rumination

subscale; alpha = 0.77 (95% CI = 0.73 – 0.82) for the magnification subscale; and alpha =

0.88 (95% CI = 0.86 – 0.9) for the helplessness subscale.

Six studies provided eight samples (n = 317) that, when weighted and combined, produced a

mean test-retest reliability of 0.88 (95% CI 0.83 - 0.93, range 0.73 – 0.97), representing good

reliability. The time lapse between the test and retest in included samples ranged from 7 to

135 days. It was not possible to test reliability of scores by time lapse as a number of studies

had a range of intervals between tests rather than a standardized interval (including one

study in which the time lapse ranged between 14-135 days).

3.5.3 Analysis of heterogeneity of PCS scores across participant groups

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Participants from studies included in this meta-analysis were categorized based on their pain

diagnosis. The ‘other’ group consisted of diagnoses that did not fit into one of the specified

categories, including participants with mixed pain diagnoses; these were excluded from

analysis of heterogeneity. The wide spread between branches in the plot of weighted mean

PCS scores suggests substantial heterogeneity in the PCS scores across participant groups

(Fig. 2). Notably, participants with lower limb pain experienced, on average, lower pain

catastrophizing than healthy participants by two points out of a possible score of 52 on the

PCS, and the mean PCS scores of participants with upper limb or upper and lower limb pain

were equivalent to those of healthy participants.

[Insert Fig. 2 here] Forest plot showing the weighted mean ES and confidence intervals of PCS

scores for groups of participants based on pain diagnosis.

3.5.4 Subgroup analysis

Owing to the extent of heterogeneity between PCS scores of participants with different pain

diagnoses, subgroup analysis was conducted to establish the heterogeneity of scores within

diagnoses, to distinguish it from sampling error [6] (Table 2). I2 values ranged from 92.27%

to 99.04%, indicating high levels of heterogeneity within diagnostic groups; 193 groups

(24,546 participants) fell into ‘other’/healthy/groups with mixed or unclear diagnoses and

were excluded from this analysis.

Subgroup analysis between study types showed considerable overlap and homogeneity in

mean PCS scores, with the exception of non-randomized controlled trials which had a higher

mean PCS score than the grand total PCS score (27.55, 95% CI 24.15 - 30.95 compared to

20.22, 95% CI 19.44 - 21). This may be an artifact of data coming from two groups within

one study which recruited participants only if they ‘reported high levels of pain

catastrophizing’ [21] (p.859),

[insert Table 2 here]

3.5.5 Meta-regression of PCS scores

Multivariate meta-regression analysis was conducted to establish the association between

PCS scores and characteristics of study participants (age, sex, diagnostic category) and study

design (language of PCS, type of study, year of study publication). After exclusion because

of missing data 277 groups were included in the analysis. Diagnostic category of

participants, language, and type of study were all significantly associated with the mean PCS

score obtained (Table 3). In a further meta-regression conducted with the variable of

diagnostic category, this variable was again significantly associated with the mean PCS

score (all 329 participant groups were included in this analysis; see Table 4).

[insert Tables 3 and 4 here]

Significantly higher or lower mean scores occurred for some non-English language versions

of the PCS, notably for the Cantonese version of the PCS (weighted mean score for

Cantonese was 36.3, compared to a mean of 18.48 for English versions, β 15.31, p = .002).

The Cantonese scores were based on one study using the Cantonese language version.

3. Discussion

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4.1 Psychometric properties of the PCS

The review included 220 studies of a total of 329 participant groups (42,976 clinical and

non-clinical participants) with a mixture of pain diagnoses, age, and gender distributions,

with a range of study types. Systematic review and meta-analytic methods were used to

synthesize existing data by establishing and refining the known psychometric properties of

the PCS using a far larger data set than previous studies. Internal consistency and test-retest

reliability of the overall score and of the rumination subscale (but not of magnification or

helplessness subscales), were all >0.85, encouraging confidence in use (see also Sullivan

and colleagues [23]). The higher test-retest reliability found in this meta-analysis than

previously [23] could be explained by shorter intervals between testing, or the inclusion in

the current meta-analysis of stabler non-clinical samples alongside clinical samples. The

psychometric findings on the PCS from a much larger evidence base may in part allay

concerns over the ‘ad-hoc’ creation of psychometric self-report scales in health and

psychology [15].

4.2 The relationship between PCS scores and participant characteristics

Subgroup analysis showed that PCS scores did not differ systematically with age or gender,

again encouraging confidence in use,,particularly in the light of contradictory results of

previous studies [1; 4; 11; 12; 22; 23; 24; 26; 27]. However, different pain diagnoses were

associated with differences in PCS scores, and while this could be mediated by the

association of pain catastrophizing scores with pain intensity reports [20], it is more likely

that different pain problems are associated with different specific worries, and those with

diagnoses that are difficult to establish or contested (such as fibromyalgia [31]) may more

consistently generate catastrophic thinking. This requires further investigation.

The findings of this review reveal differences in PCS scores across populations and

languages, but given the complexity of cultural and linguistic translation, it would be

premature to try to interpret these findings. They do, however, serve as a reminder that

simply translating a questionnaire does not guarantee that its psychometric properties remain

the same as in the original language.

4.3 Strengths and limitations of the review

Strengths and limitations of this review are considered within a broader synthesis of the use

of meta-analysis to establish psychometric properties of a self-report scale. Studies were

included in this review if PCS use was reported in the study abstract, so it is likely that some

studies were missed that only identified PCS use in their Methods. A replication could

search all papers likely to be potentially eligible; this would likely be over 3000 papers.

However, for this review, maximum use of included studies was made by including all data

available per analysis. Additionally, the principle of assessing rather than selecting against

methodological deficiency allowed the inclusion of all studies regardless of risk of bias,

examined instead by sensitivity analysis and by weighting scores using a random effects

model in the meta-analysis.

In this review, participants were categorized according to a single pain diagnosis, but many

people with chronic pain have more than one pain condition, and could not be fitted into a

pain diagnosis category. Studies used different ways of categorizing pain or describing pain

diagnoses, meaning that data were matched to ‘best fit’ for this meta-analysis, for example

‘low back pain’, ‘acute low back pain’, ‘chronic low back pain’, and ‘persistent non-specific

low back pain’ were classified as ‘lumbar pain’ although there may have been differences in

diagnosis and threshold for classification in the different studies. The high proportion of

‘healthy’ participants in included studies who were students limits the generalizability of the

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results to the general population of ‘healthy’ people without a pain diagnosis but with a

wider age range. This is not unique to this review.

It is possible that the decision to include other language versions of the PCS introduced

biases and inaccuracies owing to different psychometric properties of these versions. The

decision was justified by the widespread international use of the PCS, highlighting the need

for further validation studies of the translated versions of the questionnaire.

The risk of bias screening was completed by one author (CW). Optimally, a second author

would duplicate the screening and results would be compared. Otherwise, established

protocols for systematic review and meta-analysis were followed [14]. Meta-analytic

methods were used to correct for measurement artifacts within included studies by weighting

scores to obtain more accurate estimated effect sizes.

Samples used in the regression analysis were not fully independent in that, frequently, more

than one participant group was included from a single study. This increased the number of

groups available to analyze, but the results should be treated with caution due to this non-

independence of samples.

Even excellent reliability does not imply validity of the concepts, and there are theoretical

concerns about notions such as ‘magnification’ that imply contrast with a ‘correct’ amount

of pain experience that are inconsistent with current understanding of pain psychology.

Conclusions drawn in this review about psychometric properties of the PCS cannot be used

as proof of validity of the concept of pain catastrophizing.

Overall, this review demonstrates a comprehensive attempt to identify relevant papers and a

systematic method of discussing and deciding on inclusion and exclusion of studies. The use

of meta-analysis across a large sample of studies allowed for exploration of narrow variance

of PCS scores. The findings provide greater support for evidence from previous individual

studies on the reliability and validity of the PCS.

4.4 Implications for clinical practice and research

Studies in this meta-analysis highlighted that the PCS is widely used for research and

clinical practice. Current normative values and clinical cut-off scores are based on a sample

of 851 injured workers, 75% of whom had a soft tissue back injury [23] (p. 6). This meta-

analysis demonstrated that percentile scores as used to establish this clinical-cut-off vary

between clinical groups based on pain diagnoses. This brings into question the concept of a

clinically relevant score: should the clinical cut-off for pain catastrophizing be based on

percentiles across pain diagnoses, or is it more pertinent to establish a cut-off using

comparisons with others who have a similar pain condition? Either of these options is likely

to be preferable to using the current clinical cut-off based on one study of a sample of

injured workers. Further research is necessary to establish percentile PCS scores either

across or within pain conditions using raw scores from multiple studies.

Changes from baseline PCS scores following treatment such as surgery or psychological

therapy were not considered in the scope of this review. However, the more precise

estimates provided here for internal consistency and test-retest reliability allows calculation

of reliable change beyond that attributable to random variation across time. Meta-regression

following systematic review helped to refine participant variables that did (language; pain

diagnosis) and did not (age; gender) relate to PCS scores over a wide population. This helps

to define variables of interest for future studies of the PCS and pain catastrophizing.

Finally, the methods used in this meta-analysis could be applied to any self-report scale

(PROM) used in clinical psychology or other fields. The use of meta-analysis to establish a

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stronger evidence base for the psychometric properties of questionnaires is encouraged in

order better to understand sources of variance. This would strengthen the use of those self-

report scales, as well as encouraging discarding those that fail standards of reliability and

validity. Such research could help to introduce greater precision and theoretical justification

to the ever-increasing aggregation of concepts and scales.

4. Conclusion

This is the first psychometric meta-analysis of the PCS, and the first investigation of the PCS

on such a large scale. Meta-analytic methods in this review confirmed the reliability of the

overall scale and refined psychometric and normative properties. The PCS as a full scale is

concluded to be a reliable measure. Caution is urged in the clinical interpretation of scores

due to differences in scores between people with different pain diagnoses, and potential

linguistic or cultural influences on PCS scores should be considered when using different

language versions of the scale. It is hoped that results from this review will encourage the

use of meta-analytic methods to establish more accurate psychometric properties of other

psychological and self-report scales.

Acknowledgements

Professor Robert West, Dr Gary Latchford and Dr Andrew Prestwich are acknowledged for

their technical help with statistical analysis and interpretation.

Conflicts of interest

The authors have nothing to disclose.

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and Human Services 2014. Available: https://www.nhlbi.nih.gov/health-topics/study-quality-

assessment-tools. Accessed 30 Jul 2018.

[17] Osman A, Barrios FX, Gutierrez PM, Kopper BA, Merrifield T, Grittmann L. The Pain

Catastrophizing Scale: further psychometric evaluation with adult samples. J Behav Med

2000;23(4):351-365.

[18] Osman A, Barrios FX, Kopper BA, Hauptmann W, Jones J, O'neill E. Factor structure,

reliability, and validity of the Pain Catastrophizing Scale. J Behav Med 1997;20(6):589-605.

[19] Pedler A. The Pain Catastrophising Scale. J Physiother 2010;56(2):137.

[20] Quartana PJ, Campbell CM, Edwards RR. Pain catastrophizing: a critical review.

Expert Rev Neurother 2009;9(5):745-758.

[21] Riddle DL, Keefe FJ, Nay WT, McKee D, Attarian DE, Jensen MP. Pain coping skills

training for patients with elevated pain catastrophizing who are scheduled for knee

arthroplasty: a quasi-experimental study. Arch Phys Med Rehabil 2011;92(6):859-865.

[22] Rivest K, Côté JN, Dumas J-P, Sterling M, De Serres SJ. Relationships between pain

thresholds, catastrophizing and gender in acute whiplash injury. Man Ther 2010;15(2):154-

159.

[23] Sullivan MJ, Bishop SR, Pivik J. The pain catastrophizing scale: development and

validation. Psychol Assess 1995;7(4):524.

[24] Sullivan MJ, Neish NR. Catastrophizing, anxiety and pain during dental hygiene

treatment. Community Dent Oral Epidemiol 1998;26(5):344-349.

[25] Sullivan MJ, Thorn B, Haythornthwaite JA, Keefe F, Martin M, Bradley LA, Lefebvre

JC. Theoretical perspectives on the relation between catastrophizing and pain. Clin J Pain

2001;17(1):52-64.

13

[26] Sullivan MJ, Tripp DA, Rodgers WM, Stanish W. Catastrophizing and pain perception

in sport participants. J Appl Sport Psychol 2000;12(2):151-167.

[27] Sullivan MJ, Tripp DA, Santor D. Gender differences in pain and pain behavior: the

role of catastrophizing. Cognit Ther Research 2000;24(1):121-134.

[28] Van Damme S, Crombez G, Bijttebier P, Goubert L, Van Houdenhove B. A

confirmatory factor analysis of the Pain Catastrophizing Scale: invariant factor structure

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[31] Wolfe F. Criteria for fibromyalgia? What is fibromyalgia? Limitations to current concepts of fibromyalgia and fibromyalgia criteria. Clin Exp Rheumatol. 2017; 35(Suppl 105):S10-12.

14

Fig 1

Records identified through database searching

(n = 7,614)

Scre

enin

g

Incl

ud

ed

Elig

ibili

ty

Iden

tifi

cati

on

Records after duplicates removed (n = 3,721)

Records screened (n = 3,721)

Records excluded (n = 3,292)

Full-text articles assessed for eligibility

(n = 429)

Full-text articles excluded (n = 209)

Studies included in meta-analysis

(n = 220)

PsycINFO: 1171

EMBASE: 1584

PubMed: 953

CINAHL: 658

Cochrane Library: 334

Web of Science: 2914

16

Table 1. Weighted mean PCS scores and confidence intervals for all studies included in the

meta-analysis, for studies meeting all risk of bias criteria, and for studies that did not meet all

risk of bias criteria.

Included studies N Weighted

mean PCS

score

95% CI

of mean

Weighted sd of

PCS score

95% CI of

sd

All studies 220 20.2 19.3-21.1

10.3 10.0-10.5

Studies meeting all

risk of bias criteria

70 22.8 20.9-24.6 10.8 10.4-11.2

Studies not meeting

all risk of bias criteria

150 19.1 18.2-20.1 10.0 9.7-10.3

17

Table 3. Association between covariates in meta-regression and the grand mean PCS score.

Variable Type

III sum

of

squares

Degrees

of

freedom

Mean

square

F Significance

level

Amount

of

variance

accounted

for (eta

squared)

Mean age of

participants

118.00 1 118.00 3.15 .077 0.01

Percentage of female

participants

31.52 1 31.52 0.84 .360 0.00

Diagnostic category

of participants

5644.69 8 705.59 18.83 <.001 0.39

Language of PCS

administered

3870.13 19 203.69 5.44 <.001 0.30

Type of study 1586.30 7 226.61 6.05 <.001 0.15

Year range of

publication*

299.21 4 74.80 2.00 .096 0.03

* Year of publication was categorized into groups of 3-year duration

18

Table 4. Regression of variable ‘diagnostic category of participants’ onto the grand mean

PCS score.

Univariate

model

Weighted least squares meta-regression model

95% confidence

interval

Variable p β Lower

bound

Upper

bound

t p

Diagnostic

category of

participants

<.001

Healthy Index

Generalised pain 17.24 14.41 20.07 11.99 <.001

Head and neck pain 6.70 2.61 10.80 3.22 .001

Cervical and

thoracic pain

6.16 0.56 11.76 2.16 .031

Upper limbs or

upper and lower

limb pain

-3.40 -6.23 -0.57 -3.36 .019

Trunk pain 11.26 6.42 16.10 4.58 <.001

Lumbar pain 6.96 4.74 9.17 6.18 <.001

Lower limbs -2.16 -6.33 2.01 -1.01 .309

19

Other or mixed

diagnosis

8.25 6.44 10.07 8.94 <.001

Supplementary files

Suppl. Figure 1. Search strategy used to identify potentially relevant studies from the

Cochrane Library.

1. pain catastrophi* scale*

2. pain catastrophi* measure*

3. pain catastrophi* questionnaire*

4. catastrophization [MeSH terms]

5. pain measurement [MeSH terms]

6. pain NEAR/3 catastrophi*

7. #4 AND #5

8. #1 OR #2 OR #3 OR #6 OR #7

20

Suppl. Table 1. Characteristics of studies included in the review and meta-analysis.

Study

ID

First

author

Year

of

public

ation Study type Language Participant group

Sample

size

Mean

age Sd age

M:F

participa

nts

Mean

PCS

score

Sd PCS

score

3 Barke 2015 Psychometric German Chronic back pain 182 51 10.5 54:128 19.7 12.1

6 Iwaki 2012 Cross Japanese Chronic pain 160 51 16.4 48:112 33.9 10.2

7 Karstens 2015 Psychometric German Lower back pain 228 42 11 120:128 16.7 10.5

8 Kikuchi 2015 Cross Japanese

Whiplash neck injury

pain and/or low back

pain 956 45 10.4 679:277 24 11.8

9 Kim 2013 Psychometric Korean

Degenerative spinal

disease 72 66 8.1 27:45 24.1 12.2

10 Kjogx 2014 Cross Danish Chronic headache 57 49 15.1 57:0 16.9 10.4

10 Kjogx 2014 Cross Danish Chronic headache 161 45 15.2 0:161 22.5 12

10 Kjogx 2014 Cross Danish Healthy participants 118 22 7.2 118:0 10.3 6.7

21

10 Kjogx 2014 Cross Danish Healthy participants 129 22 5.2 0:129 12.3 8.7

11 Koo 2015 Psychometric Korean Chronic pain 64 41 14.5 23:41 18.8 11.9

12 Kraljevic 2012 Cross Croatian Chronic pain 100 55 10 36:64 31 12.6

12 Kraljevic 2012 Cross Croatian

Healthy participants

(adult children) 100 30 10 50:50 21.8 12.2

12 Kraljevic 2012 Cross Croatian


(spouse) 85 60 10 51:34 25.6 13.4

16 Lim 2006 Psychometric Chinese Chronic pain 120 / / 50:70 31.9 11.1

17 Lopes 2015 Psychometric

Brazilian

Portuguese Acute low back pain 131 67 7.1 10:121 29.2 13.1

18 Man 2007 Case Chinese Chronic pain 45 / / 15:30 33.7 12.1

19 Maric 2011 Cross Croatian


6th yr medical

students 53 24 1.8 10:43 16.8 9.9



1st yr medical

students 137 19 1.7 47:90 19.2 7.9

22



1st yr economics

students 245 19 1.7 86:159 19.7 9.1



5th yr economics

students 86 23 1.7 22:64 19.8 10.1

20 Matsudaira 2014 Psychometric Japanese Low back pain 1786 49 / 900:886 24.6 10.9

21 Matsuoka 2010 Case Japanese

Burning mouth

syndrome 46 60 9.6 2:44 28.2 9.7

23 Meyer 2008 Psychometric German Low back pain 111 49 16 36:75 17.6 10.5

25 Mohd Din 2015 Psychometric Malay


military 303 21 1.8 258:45 19.2 10.2

29 Morris 2012 Psychometric Africaans

Fibromyalgia,

Africaans speaker 41 / / / 37 11.4

29 Morris 2012 Psychometric

English

South

African

Fibromyalgia,

English speaker 33 / / / 38.2 11.5

23

29 Morris 2012 Psychometric Xhosa

Fibromyalgia, Xhosa

speaker 19 / / / 34.2 8.5

30 Ning 2008 Psychometric Cantonese Chronic pain 224 42 10.3 120:104 36.3 10.9

35 Penhoat 2014 Cross French Rheumatoid arthritis 86 59 13.7 27:59 17 13.6

35 Penhoat 2014 Cross French Spondyloarthritis 54 43 10.1 37:17 20.8 12.1

37 Rodero 2010 Psychometric Spanish Fibromyalgia 205 50 9.7 19:186 32.4 12.8

38 Rodero 2012 Psychometric Spanish Fibromyalgia 250 52 8.5 11:239 24.3 13.6

40 Roelofs 2003 Psychometric Dutch Fibromyalgia 401 48 10.1 22:379 20.3 11.5

41 Roelofs 2002 Psychometric Spanish


students 271 19 1.4 54:226 14.3 7.9

42 Rogulj 2014 Cross Croatian

Burning mouth

syndrome 30 66 9.2 5:25 28.4 15

43 Sehn 2012 Psychometric

Brazilian

Portuguese

Chronic

musculoskeletal pain 384 50 17.1 67:317 30.6 11.7

44 Severijns 2002 Cross Dutch Hip/knee pain 582 / / / 12.1 10.4

44 Severijns 2002 Cross Dutch Low back pain 754 / / / 12.2 10.4

24

44 Severijns 2002 Cross Dutch

Neck/shoulder/high

back pain 880 / / / 12.3 10.3


Elbow/wrist/hand

pain 480 / / / 13 10.8

44 Severijns 2002 Cross Dutch Ankle/foot pain 284 / / / 13.5 11


Healthy participants,

no pain 1164 / / / 8.2 8

46 Suren 2014 Cross Turkish Preoperative patients 165 39 13.9 91:74 16.1 11.5

48

Van

Damme 2002 Psychometric Dutch Low back pain 162 42 11.6 63:99 22 9.3

48

Van

Damme 2002 Psychometric Dutch Fibromyalgia 100 45 9.1 20:80 24.8 12.2

48

Van

Damme 2002 Psychometric Dutch


students 550 19 1.4 147:403 16.6 7.8

49 Volz 2013 Series

Brazilian

Portuguese

Chronic myofascial

pain syndrome 24 48 12.6 0:24 34.2 9.2

50 Wong 2015 Series Chinese Chronic pain 226 45 9.2 77:149 26.7 14.7

25

51 Wong 2011 Psychometric Chinese

Chronic

musculoskeletal pain 208 41 11.3 95:113 29 14.3

54 Yap 2008 Psychometric Chinese

Chronic

nonmalignant pain 130 / / 54:76 29.1 5.5

56 Park 2015 Cross Korean

Temporomandibular

disorder 155 39 15.2 44:111 17.3 12.6

65 Adachi 2014

Cross-

sectional study Japanese Chronic pain 176 64 15.1 80:96 26.5 12.2

66 Aerts 2015 Cohort study English

Secondary provoked

vestibulodynia 175 28 5.5 0:175 26.7 10.7

66 Aerts 2015 Cohort study English

Primary provoked

vestibulodynia 94 26 5.5 0:94 27.6 10

67 Akhter 2014 Other English Healthy participants 28 35 9.5 20:8 15.4 11.4

69 Alappattu 2015 Cross English Pelvic pain 14 40 / 0:14 23.1 12.4

69 Alappattu 2015 Cross English Healthy participants 28 30 / 0:28 9.2 9.7

70 Albert 2015 Cohort study French

Musculoskeletal

disorder 43 41 12 20:23 19 12

26

71 Al-Kaisy 2015

Retrospective

cohort stud English

Chronic neuropathic

pain of upper or

lower limbs 11 46 12 5:6 33 11

75 Archer 2015 Cohort English

Lower extremity

trauma 134 45 15 70:64 14 13

77 Baranoff 2015 Cohort English

Anterior cruciate

ligament

reconstruction 44 27 9.4 27:17 11.3 9.8

78 Barnhoorn 2015

RCT

secondary data

analysis Dutch

Complex Regional

Pain Syndrome type

1 35 43 16.9 6:29 22.8 11.7

78 Barnhoorn 2015

RCT

secondary data

analysis Dutch

Complex Regional

Pain Syndrome type

1 21 46 16.5 5:16 24.9 14.8

81 Beck 2014 Series English

Orthodontic

elastomeric

separators 20 24 3.4 9:11 14.6 7.6

27

86 Beneciuk 2013 Series English Low back pain 146 41 13.5 57:89 16.8 12.1

87 Beneciuk 2012

Secondary

analysis English

Acute and subacute

low back pain 108 37 14.5 39:69 16.3 11.2

90

Bhaskarac

harya 2015 Cross English

Pain-free participants

with a history of

chronic trigeminal

neuropathic pain 12 64 9.5 0:12 15.9 13.3

90

Bhaskarac

harya 2015 Cross English


control group 15 62 6.9 4:11 7.1 11.7

91 Billis 2013 Cross English

Non-specific low

back pain 106 36 15.9 43:63 19.4 7.9

92 Block 2008 Cross English Chronic pain 43 44 12.7 17:26 23.9 11.8

94 Bond 2015 Series English Migraine and obesity 105 38 8 0:105 22.7 10.8

96 Borg 2012 Cross Dutch Dyspareunia 33 27 6.8 0:33 15.3 7.3

96 Borg 2012 Cross Dutch Vaginismus 35 28 5.8 0:35 22 9.3

28

96 Borg 2012 Cross Dutch


without sexual

complaints 54 27 6.7 0:54 17.4 9.1

98 Bostick 2013 Series English

Whiplash associated

disorder 72 39 14 15:57 24.7 9.4

99 Bot 2014 Psychometric English

Upper extremity

diagnoses 164 51 15 75:89 5.3 6.9

101 Bot 2013 Series English

Post patients hand

surgery

nonresponders to

later survey 69 48 16 37:32 3.2 4.9

101 Bot 2013 Series English

Post patients hand

surgery responders to

later survey 35 56 17 10:25 5.6 7.2

102 Bot 2014 Cross English

Painful conditions of

the upper extremity 130 52 16 62:68 8.7 9.4

29

103 Bot 2013 Cohort English

Arm, shoulder and

hand disability 1204 53 16 511:693 6.8 8.4

108 Brandini 2011 Case English

Temperomandibular

disorder 15 31 10.7 0:15 12.7 10.6

108 Brandini 2011 Case English Healthy participants 14 29 5 0:14 11 8.4

114 Bryson 2014 Cross English

Chronic pain and

insomnia 111 44 10.9 35:76 30.6 14.7

116 Buitenhuis 2008 Series English

Postwhiplash

syndrome 140 36 12 45:95 12.9 11.3

119 Calley 2010 Cross English Low back pain 80 47 11.5 34:46 13.9 10.1

120 Campbell 2010 Case English

Temperomandibular

joint disorder 48 34 12 7:41 14.3 9.2

120 Campbell 2010 Case English Arthritis 43 55 9.7 16:27 15.4 12

120 Campbell 2010 Case English Healthy participants 84 34 14.6 51:33 9.5 9

123 Carroll 2011 Case English

Palliative care

patients on opioid

treatment 20 58 10 9:11 19.8 13.3

30

125 Carvalho 2014 Series English

Labour and

successful vaginal

delivery 39 34 5 0:39 16 9

128 Casey 2015 Cohort English Whiplash injury 246 43 14.6 54:192 16.1 13.2

130 Cebolla 2013 Psychometric Spanish Fibromyalgia 251 52 8.4 10:241 24.3 13.6

135 Chatkoff 2015 Cross English

Muskuloskeletal

pain, adaptive copers 26 / / / 20.3 13.9


Muskuloskeletal

pain, dysfunctional 15 / / / 27.8 12.8


Muskuloskeletal

pain, dysfunctional 28 / / / 32.5 10.1

138 Chibnall 2005 Psychometric English

Low back injury,

compensation

claimants 1475 / / 919:556 25.4 12.1

140

Choobmasj

edi 2012 Cross Arabic

Healthy volunteers

pregnant 300 28 5.9 0:300 29.3 11.8

31

142 Chung 2012 Series Chinese

Major depressive

disorder 91 48 9.5 18:73 23.7 13.1

143 Chung 2015 Other Chinese

Major depressive

disorder 137 50 9.6 28:109 24.6 11.3

149 Cosic 2013 Cohort Croatian Parous 69 30 / 0:69 16.1 13.2

149 Cosic 2013 Cohort Croatian Nulliparous 80 24 / 0:80 23.9 12.6

151 Curran 2010 Series English

Provoked

vestibuladynia 8 30 10.6 0:8 24.8 7.9

153 Darchuk 2010 Series English

Non-cancer pain,

geriatric patients,

older 78 67 5.6 28:50 25.6 13.7


Non-cancer pain,

geriatric patients,

middle aged 230 48 5.3 43:187 26.2 12.1


Non-cancer pain,

geriatric patients,

younger 141 30 6.2 25:116 27.3 12.6

32

154 Darnall 2012 Cross English

Chronic pain,

incarcerated women 159 39 11.5 0:159 27.1 11.8

155 Darnall 2014 Series English

Chronic pain

outpatients 57 50 12.2 16:41 26.1 10.8

159 Davidson 2008 Psychometric English Chronic pain 126 50 14.2 40:86 22.4 13.2

161 Davis 2015 Series English

Provoked

vestibulodynia 222 31 10.9 0:222 28.2 10.8

165 de Boer 2014 Cross Dutch

Chronic pain,

outpatients 89 51 15.5 34:55 22.4 13

172 Demoulin 2010 Psychometric Dutch

Chronic low back

pain 99 42 9.4 60:39 22.2 10.3

173 D'Eon 2004 Psychometric English


students, men 229 21 3.7 229:0 20.6 9.6

173 D'Eon 2004 Psychometric English


students, women 276 20 4.1 0:276 26.4 9.4

176 Dimitriadis 2014 Psychometric Greek Chronic neck pain 45 36 14.5 13:32 21.4 12

33

179 Dixon 2004

Other

experimental English


college students, men 91 / / 91:0 16.6 7.9

179 Dixon 2004

Other

experimental English


college students,

women 112 / / 0:112 19.2 9.7

185 Durosaro 2008 Series English Erythromelalgia 8 43 16.8 1:7 29.9 6.8

191 Fabian 2011 Cross English



191 Fabian 2011 Cross English


college students 62 / / 24:38 15.9 8.2

193 Feldman 2015 Cross English

Patients undergoing

total knee

arthroplasty 316 66 8.7 130:186 12 10.7

195 Fernandes 2002 Psychometric Norwegian

Non-specific low

back pain 90 48 11.7 38:52 13.6 9.2

197 Fitzcharles 2014 Cross English Fibromyalgia 246 48 10.4 22:224 29.3 12.2

199 Flink 2009 Series Swedish Prepartum 82 / / 0:82 19.6 9.5

34

200 Forsythe 2008 Series English

Preoperative patients

before total knee

arthroplasty 55 69 8.4 20:35 9.8 8.7

201 Fritz 2015 Rct English

Recent-onset low

back pain 112 37 10.2 59:53 13.8 10.1

201 Fritz 2015 Rct English

Recent-onset low

back pain 108 38 10.4 46:62 13.9 11

202 Gagnon 2013 Series English Chronic pain 101 44 8.2 64:37 28 15

203 Gandhi 2010 Psychometric English Hip osteoarthritis 100 63 10.6 50:50 16.6 13.7

203 Gandhi 2010 Psychometric English Knee osteoarthritis 100 67 8.4 31:69 17.3 13.3

205

Garcia-

Campayo 2010 Psychometric Spanish Fibromyalgia 250 45 7.2 21:229 30.8 11.7

206 Herbst 2010 Series English Adiposis dolorosa 10 48 3.6 4:6 28.2 3.5

207 Gautier 2011 Cross Other Chronic pain, men 26 41 8 26:0 23.7 9.4

207 Gautier 2011 Cross Other Chronic pain, women 24 39 10.6 0:24 27.1 13.1

209 George 2011 Psychometric English Low back pain 80 47 11.5 34:46 14.1 10.1

35

212 Geva 2013 Case English


triathletes 19 40 12.1 11:8 16.5 9

212 Geva 2013 Case English


controls 17 37 11.1 7:10 20.8 12

214 Gilliam 2010 Cross English Healthy participants 97 25 2.8 41:56 19.5 8.8

215 Goodin 2011 Other English


college students,

Caucasian American 86 / / / 13.2 8.6



college students,

African American 28 / / / 15.4 11.5



college students,

Asian American 35 / / / 15.9 9.9

219 Grotle 2012 Psychometric Norwegian

Pelvic girdle pain in

pregnancy and after

delivery 87 34 5.3 0:87 13.5 8.7

36

223 Hayashi 2015 Series Japanese Neck-shoulder pain 87 51 16.4 35:52 32.1 10.6

223 Hayashi 2015 Series Japanese Headache 62 51 18.3 14:48 33.7 10.3

223 Hayashi 2015 Series Japanese

Low back/lower limb

pain 142 57 15 58:84 33.7 10.1

224 Hegarty 2014 Cross English

Post-enucleation,

persistent pain 8 61 18.1 6:2 3.6 6.8

224 Hegarty 2014 Cross English

Post-enucleation, no

pain 9 61 18.2 3:6 6.8 15.9

228 Hiebert 2012 Series English

Low back pain,

active duty US navy

personnel 253 32 7.9 188:65 11.1 9.9

229 Hirakawa 2014 Series Japanese

Patients three weeks

post surgery 90 76 6.3 20:70 13 9.3

230 Hirsch 2008 Psychometric English


undergraduate

students 100 21 1.7 44:66 18.6 9.2

37

235 Hooten 2009 Cohort English

Chronic pain, never

smoked, male 134 47 13.6 134:0 23.1 12.3


Chronic pain, never

smoked, female 500 46 4.8 0:500 24.8 13


Chronic pain, former

smoker, female 203 50 12.9 0:203 26 11.9


Chronic pain, former

smoker, male 91 54 13.5 91:0 26.2 11.1


Chronic pain,

smoker, female 225 43 10.9 0:225 27.6 13.2


Chronic pain,

smoker, male 88 42 12 88:0 31.5 11

238 Horsham 2013 Cross English

Experienced trauma

but no PTSD 91 / / / 13.6 7.8

238 Horsham 2013 Cross English

Control (no

experience of

trauma, no PTSD) 71 / / / 8.6 4.3

38

238 Horsham 2013 Cross English Ptsd 87 / / / 25.3 8

241 Kadimpati 2015 Cross English Chronic pain 595 47 13.7 173:422 26.7 11.2

242 Kao 2012 Cross Other

Postmenapausal

dyspareunia sufferers 182 57 5.4 0:182 16.1 13.2

244 Karayannis 2013 Cross English Low back pain 19 43 13.2 6:14 14.4 8.2

246 Karsdorp 2009 Cross Dutch Fibromyalgia 409 48 10.2 21:388 20.3 11.4

252 Khan 2012 Series English

Cardiac surgery,

preoperative 64 66 11.1 54:10 11.7 11.1


Degenerative lumbar

spinal stenosis, men 35 64 12.8 35:0 19.9 13.3


Degenerative lumbar

spinal stenosis,

women 60 66 9.6 0:60 27.9 11.5

254 Kim 2014 Cross Korean

Lumbar spinal

stenosis 155 65 12.4 57:98 24.9 12.8

256 Kleiman 2011 Psychometric English

Patients scheduled

for major surgery 444 46 10.2 174:270 16.5 10.5

39

257 Koele 2014 Series Dutch

Chronic widespread


260

Kristjansd

ottir 2013 Rct Norwegian

Chronic widespread

pain 66 44 11.2 0:66 20.8 9.5

260

Kristjansd

ottir 2013 Rct Norwegian

Chronic widespread

pain 69 45 11.1 0:69 21.2 10.3

263 La Touche 2014 Cross Spanish

Chronic craniofacial

pain 192 46 13.1 60:132 23.9 8.9

264 Lame 2008 Psychometric Dutch Chronic pain 50 55 13.1 20:30 30.2 11.7

265 Lariviere 2010 Cohort English

Chronic low back

pain, women 13 35 9 0:13 15 13

265 Lariviere 2010 Cohort English

Chronic low back

pain, men 14 43 10 14:0 26 10

268 Lee 2008 Psychometric English Healthy participants 189 27 8 99:90 11.4 7.4

269 Lemieux 2013 Cross French Dyspareunia 179 31 10 0:179 28.6 9.7

270 Leonard 2013 Cross English

Chronic


40

271 Lin 2013 Other Chinese Healthy participants 15 26 11.2 6:9 19.2 8.1

272

Lindenhov

ius 2008 Rct English

Lateral elbow pain,

placedo, lidocaine

only 30 51 10 12:18 20.8 8.5

272

Lindenhov

ius 2008 Rct English

Lateral elbow pain,

dexamethasone 27 50 8 10:17 21.8 10.5

274 London 2014 Cohort English

Atraumatic hand or

wrist condition 256 56 12.6 75:181 11.8 8.9

275 Louw 2015 Series English

Patients scheduled

for lumbar surgery 10 47 16.2 3:7 25.4 13.5

280 Lukkahatai 2013 Cross English

Fibromyalgia

patients with fatigue 9 41 7.3 0:9 17 9.8

282 Theunissen 2014 Psychometric Dutch

Preoperative

hysterectomy 192 46 7.8 0:192 13.1 8.5

282 Theunissen 2014 Psychometric Dutch

Patients undergoing

day surgery,

preoperative 75 53 15.3 31:44 14 8.8

41

282 Theunissen 2014 Psychometric Dutch Mixed inpatient 1490 56 15.5 702:788 16.5 12.7

283 Martel 2013 Series English Chronic pain, women 35 50 8.9 0:35 24.3 13.6

283 Martel 2013 Series English Chronic pain, men 20 49 10.5 20:0 24.5 10.4

284 Martin 2010 Cross English

Chronic pain patients

pre-surgery 208 47 9.7 83:124 19.3 7.9

285 Martinez 2012 Cross Spanish Healthy participants 200 40 11.3 0:200 13.7 10

288

Masselin-

Dubois 2013 Cohort French

Breast cancer

patients pre-surgery 100 55 12.1 0:100 14.6 11.4

288

Masselin-

Dubois 2013 Cohort French

Total knee

arthroplasty patients

pre-surgery 89 69 8.9 35:65 19.4 11.2

290

McLoughli

n 2011 Cross English

Women with

fibromyalgia 39 43 12.1 0:39 13.9 7.7

290

McLoughli

n 2011 Cross English

Women healthy

controls 40 41 9.1 0:40 8.5 7

291

McWillia

ms 2007 Psychometric English


university students 278 20 4 145:136 15.7 9

42

292

McWillia

ms 2015 Psychometric English Chronic pain 201 47 10.3 74:127 25.8 12

293 Meeus 2010 Rct Dutch

Chronic fatigue

syndrome and

chronic widespread

pain, experimental

group 24 38 10.6 2:22 18.2 6.9

293 Meeus 2010 Rct Dutch

Chronic fatigue

syndrome and

chronic widespread

pain, control group 24 42 10.2 6:18 21.8 8.9

294 Meyer 2009 Cross German

Chronic low back

pain 78 50 17 26:52 19.2 10.3

295 Michael 2004 Series English Chronic pain 86 42 10.4 46:40 27 13.3

298 Monticone 2014 Rct Italian

Chronic low back

pain, control group 10 57 14.4 6:4 23 4

43


Chronic low back

pain, experimental

group 10 59 16.4 3:7 25 6


Spondylolisthesis

and/or lumbar spinal

stenosis,

experimental group 65 59 11.8 21:44 24.8 9.3


Spondylolisthesis

and/or lumbar spinal

stenosis, control

group 65 56 14.2 30:35 27 8.7

301 Monticone 2015 Psychometric Italian Chronic neck pain 118 48 15.9 40:78 18.5 9

302 Moore 2013 Cross English


male 70 23 6.6 70:0 18 8.6

302 Moore 2013 Cross English


female 119 24 5.9 0:119 20.5 8.3

44

303 Moseley 2004 Series English

Chronic low back

pain, group 2 46 35 7 16:30 16 5

303 Moseley 2004 Series English

Chronic low back

pain, group 1 75 36 6 38:37 16 6

304 Moseley 2004 Rct English

Chronic low back

pain, experimental

group 31 42 10 13:18 19 6

304 Moseley 2004 Rct English

Chronic low back

pain, control group 27 45 6 12:15 20 6

307 Moustafa 2015 Rct English

Fibromyalgia and

C1-2 joint

disfunction 60 51 7 33:27 42.5 3

307 Moustafa 2015 Rct English

Fibromyalgia and

C1-2 joint

disfunction 60 54 8 35:25 43.8 3.6

308 Munoz 2005 Cross Other Chronic pain 149 59 15 42:107 20.9 16.3

45

309 Nakamura 2014 Cross Japanese

Chronic pain,

receiving folk

remedy 108 46 13.8 33:75 23.2 9.9

309 Nakamura 2014 Cross Japanese

Chronic pain, seen at

medical facility 213 55 14.8 84:129 26.5 10.3

310 Naugle 2014 Other English


young adults, men 12 / / 12:0 5.2 4.1

310 Naugle 2014 Other English


young adults, women 15 / / 0:15 9.3 4.1

312 Nickel 2010 Case English

Interstitial

cystitis/painful

bladder syndrome 207 50 15.1 0:207 21.3 12.6

312 Nickel 2010 Case English


control group 117 48 13.5 0:117 9.9 9.2

314 Nieto 2011 Cross Spanish

Whiplash associated

disorders 147 34 10.4 42:105 17.9 9.9

46

316 Nishigami 2015 Case Japanese

Chronic low back

pain, shrunken

perceived body

image 12 62 12.4 4:8 19.6 11.4


Chronic low back

pain, expanded

perceived body

image 12 57 16.7 4:8 21.4 6.5


Chronic low back

pain, normal

perceived body

image 18 65 11.2 8:10 21.6 7

317 Novak 2011 Cross English

Upper-extremity

nerve injury 158 41 16 105:53 16 15

318 Novak 2012 Cross English

Brachial plexus

nerve injury 61 40 17 41:20 15 14

47

319 Novak 2013 Psychometric English

Upper extremity

nerve injury 157 41 16 104:53 16 15

321 Ogunlana 2015 Cross English

Nonspecific low

back pain 275 52 13.4 110:165 24 10.4

325 Osman 2000 Psychometric English Pain outpatients, men 26 31 8.7 26:0 19.6 11.4

325 Osman 2000 Psychometric English

Pain outpatients,

women 34 33 10.7 0:34 24.3 8.8



men 85 36 10.8 85:0 11.1 8



women 130 35 12.2 0:130 15.7 10.9



students, study 2,

men 59 20 2.5 59:0 10.9 7.8



students, study 3,

women 86 / / 0:86 11.7 8.4

48



students, study 1,

men 93 / / 93:0 11.9 8



students, study 1,

women 195 / / 0:195 14.6 9.6



students, study 2,

women 161 20 3.7 0:161 15 9.5



students, study 3,

men 86 / / 86:0 18.4 9.6

327

Papaioann

ou 2009 Series Greek

Degenerative disc

disease 61 51 14.5 25:36 21.7 13.2

328 Parr 2012 Psychometric English Healthy participants 126 24 9.8 51:75 9.8 7.8

330 Pavlin 2005 Series English

Anterior cruciate

ligament injury 48 31 1.2 27:21 14.4 8.3

49

331 Pearson 2009 Cross English

Whiplash-associated

disorder 14 37 10.8 8:6 17 14.4

333 Philips 2014 Cross English

HIV-associated

sensory

polyneuropathy 28 51 8.4 25:3 23.7 12.6

333 Philips 2014 Cross English

HIV-positive but

with no HIV-

associated sensory

polyneuropathy 38 48 8.9 32:6 14.1 11.8

334 Pincus 2008 Psychometric English

Non-cancer chronic

pain 243 44 12 110:133 29.3 12.3

335 Plazier 2015 Series Other Fibromyalgia 11 42 8.3 0:11 20.6 8.8

337 Prugh 2012 Series English

Throwing athletes

with elbow injuries 3 21 2.5 3:0 5 7

338 Pukall 2007 Series English

Vulvar vestibulitis

syndrome 8 26 5.7 0:8 18.1 6.9

50

339 Raak 2006 Cross Swedish

Whiplash associated

disorder 17 51 11.3 1:16 19.9 7.8

339 Raak 2006 Cross Swedish Healthy participants 18 45 10.2 1:17 13 5.6

340 Radat 2013 Cohort French

Chronic peripheral

neuropathic pain 182 60 13.8 87:95 28 13

341 Reyahin 2014 Psychometric English Knee osteoarthritis 212 65 10.1 49:163 6.6 7

342 Riddle 2011 Nrct English

Patients scheduled

for knee arthroplasty,

control group 45 61 9.9 12:33 25.8 11.1

342 Riddle 2011 Nrct English

Patients scheduled

for knee arthroplasty,


343 Ring 2005 Cross English

Pain, single discrete

pain complaint 56 55 15 22:34 14 11.3

343 Ring 2005 Cross English

Pain, vague diffuse

idiopathic arm pain 51 41 15 14:37 20.4 11.7

51

344 Rivest 2010 Cross English

Whiplash associated

disorder 37 35 12.2 16:21 16.4 14.2

346 Robles 2012 Series English Healthy participants 76 25 5.2 27:49 14.4 9.8

347 Rodero 2008 Series Spanish Fibromyalgia 8 / / 1:7 25.3 10

348 Rodero 2010 Cross Spanish

Fibromyalgia, under

2 years chronicity 46 47 9.8 / 30.9 14.3


Fibromyalgia, 2-4

years chronicity 59 48 11 / 33.1 11.9


Fibromyalgia, more

than 4 years

chronicity 223 50 10.5 / 33.1 11.6

349 Roh 2014 Series Korean

Patients post-surgery

distal radius fractures 121 53 14 54:67 22 9

350 Roh 2015 Series Korean

Patients with

surgically treated

hand fractures 93 45 12 55:48 23 8

52

351 Rosenberg 2015 Series English

Chronic pain of trunk

and/or limbs 386 56 14.5 156:230 30.2 12.1

353 Roth 2007 Series English

Patients pre-surgery,

total knee

arthroplasty 63 70 8.8 29:34 7.1 7.3

355

Ruiz-

Parraga 2014 Cross Spanish

Chronic

musculoskeletal pain,

non-trauma-exposed 117 43 11.7 36:81 20.5 6.5

355

Ruiz-


Chronic


trauma-exposed

without post

traumatic stress

symptoms 119 44 11.2 36:83 21 6.9

355

Ruiz-


Chronic


trauma-exposed with 110 47 12.5 30:80 31.9 10.3

53

post traumatic stress

symtoms

356

Ruschewe

yh 2011 Cross German


younger group 88 27 4.8 29:59 15.5 8.8

356

Ruschewe

yh 2011 Cross German


older group 46 60 5.2 20:26 20.2 11.2

357 Sanchez 2011 Cross Spanish Fibromyalgia 74 47 8.1 4:70 25.4 11.8

358 Sansone 2014 Cross English Primary care patients 239 46 15 88:151 13.2 13.1

366 Scott 2014 Series English

Whiplash injury,

occupationally

disabled 148 37 9.2 / 22.3 10.8

367 Selvarajah 2014 Cross English Diabetic neuropathy 142 61 11.2 80:62 18.7 9

373 Sterling 2008 Cross English Whiplash injury 30 38 11.5 7:23 18.8 12.7

373 Sterling 2008 Cross English Healthy participants 30 30 8.8 6:24 12.2 5.1

376 Sullivan 2005 Cross English

Post-herpetic

neuralgia 12 70 / 4:8 20.7 9.2

376 Sullivan 2005 Cross English Diabetic neuropathy 19 57 / 15:4 25.5 11.7

54


Post-surgical/post-

traumatic pain 49 47 / 22:27 26.2 11.9

380 Sullivan 2002 Cross English Whiplash injury 65 35 7.1 25:40 32.2 10.9


Chronic pain,

chronicity less than 2

years 44 36 7.5 / 29.1 11.3


Chronic pain,

chronicity more than

4 years 51 39 8.3 / 31.3 10.7


Chronic pain,

chronicity 2-4 years 55 34 9.2 / 31.9 11.3

382 Sullivan 2000 Other English





college students,

women 55 / / 0:55 20.5 8.9

55






college students,

women 42 / / 0:42 26.6 10.4

384 Sullivan 2008 Rct English

Post-herpetic,

diabetic, or post-

traumatic neuralgia 22 52 16.3 11:10 24.2 10.8

384 Sullivan 2008 Rct English

Post-herpetic,

diabetic, or post-

traumatic neuralgia 24 55 12.6 15:9 25.2 11.4


Soft-tissue injuries to

the neck, shoulders

or back following

work or motor

vehicle accidents 86 36 7.8 27:59 28 12.8

56

388

Swinkels-

Meewisse 2006 Series Dutch

Acute lower back

pain 93 45 11.5 45:48 18.8 12

391 Tetsunaga 2015 Series Japanese

Intractable chronic

pain, adaptive group 37 56 14 15:22 33.7 6.6

391 Tetsunaga 2015 Series Japanese

Intractable chronic

pain, dropout group 16 50 15 5:11 37.5 6.8

392 Teunis 2015 Series English

After distal radius

fracture surgery 116 55 14 31:85 17 5.9

393 Thorn 2004 Other English


students, men 90 / / 90:0 15.3 9.8

393 Thorn 2004 Other English


students, women 129 / / 0:129 21.9 10.4

394

Tomkins-

Lane 2015 Series pilot English

Lumbar spinal

stenosis 10 68 6.7 4:6 7.9 5.7

395 Torres 2015 Rct Spanish

Fibromyalgia,


57

395 Torres 2015 Rct Spanish

Fibromyalgia,

control group 24 53 7.7 4:20 28.3 12.3

396 Touche 2015 Cohort Spanish

Headache attributed

to

temporomandibular

disorder, mild neck

disability 42 41 12.9 25:17 15.8 4

396 Touche 2015 Cohort Spanish

Headache attributed

to

temporomandibular

disorder, moderate

neck disability 41 44 10.9 15:26 17.1 3.8

396 Touche 2015 Cohort Spanish Healthy participants 39 41 10 13:26 5.5 1.8

398 Trompetter 2015 Rct Dutch Chronic pain 79 52 11.8 19:60 17.6 10.2

398 Trompetter 2015 Rct Dutch Chronic pain 82 53 13.3 19:63 18.6 9.5

398 Trompetter 2015 Rct Dutch Chronic pain 77 53 12 19:58 19.1 9.6

399 Turner 2013 Cross English Rheumatoid arthritis 32 55 15.7 8:24 21 11

58

399 Turner 2013 Cross English Healthy participants 28 47 11.8 7:21 8 8

400 Vaisy 2015 Cross German Low back pain 20 33 9.6 19:11 13.9 8.9

401

van

Damme 2014 Cross English

Persistent non-

specific low back

pain, good

performers on

muscle endurance

task 120 42 8.1 / 15.9 9.3

401

van

Damme 2014 Cross English

Persistent non-

specific low back

pain,

underperformers on

muscle endurance

task 212 42 8.1 / 18.5 9.8

404

van

Ittersum 2011 Series Dutch Fibromyalgia 41 / / 3:38 15.2 11.4

59

405

van

Ittersum 2014 Rct Dutch Fibromyalgia 52 46 9.8 4:48 23 12.1

405

van

Ittersum 2014 Rct Dutch Fibromyalgia 53 48 9.1 3:50 24 11.9

407 Vancleef 2006 Cross Dutch


university local

community 48 22 4.4 12:36 14.2 7.8

410 Vincent 2014 Rct English

Obese adults with

chronic low back

pain 17 69 7.3 5:12 11.5 12.6


Obese adults with

chronic low back

pain 14 68 6.4 5:9 12.5 11.7


Obese adults with

chronic low back

pain 18 69 7.1 6:12 13.2 12.7

413 Vowles 2013 Cross English Chronic pain 334 46 11.4 126:208 25.3 17.3

60

414 Vranceanu 2014 Series English

One to two months

after muskuloskeletal

trauma surgery 136 48 17.3 63:73 19.1 8.7

415 Vranceanu 2015 Rct English

Musculoskeletal

trauma within last 1-

2 months,

experimental group 24 / / / 14.8 9.9

415 Vranceanu 2015 Rct English

Musculoskeletal

trauma within last 1-

2 months, control

group 10 / / / 15.7 11.2

418 Walker 2014 Cross English Spinal pain 183 55 14.5 116:67 15.1 10.6

420 Walton 2013 Psychometric English

Patients with work-

related pain

conditions 235 37 10 88:147 21.7 10.9

61

421 Watson 2008 Cross English

Isolated, discrete

upper-extremity

condition 134 50 13 83:51 19.3 7.3

423 Witvrouw 2009 Series Dutch

Preoperative, total

knee arthroplasty 43 61 / 17:26 20.2 9.7

424 Wong 2013 Cross Chinese Chronic pain 224 46 9.9 100:124 24.6 14.3

425 Zhao 2012 Other English


experimental group 13 30 4.9 6:7 8.2 6

425 Zhao 2012 Other English


control group 13 30 3.4 6:7 12.6 13.6

62

Suppl. Table 2. Reasons for papers not included in the database at title/abstract and full text stages.

Stage of screening Number of

papers

excluded

Reason for exclusion

Abstract and title screening (total of

3,292 papers excluded at this stage) 1079 Not enough info in title/abstract to judge inclusion and exclusion criteria

639 Not relevant (not a study/no use of PCS. Includes errata)

437 PCS not used

401 Conference or meeting abstract, not a paper

355 Relevant review/meta-analysis/editorial comment/letter/theoretical paper

210 Use of PCS, but for children/adolescents (under 18yrs); or child study (may or may not use PCS),

or parent version of PCS

100 Study protocol or dissertation abstract

34 Data only (full paper coded separately)

12 Animal study

63

10 Conference proceedings/posters

7 Book chapter or book review

3 Uses 4-question version or another modified version of PCS

2 Uses spouse version only (PCS-S)

2 Uses a modified PCS

1 Guidelines (not a study)

Full text screening (total of 209 papers

excluded at this stage) 52 PCS scores not reported

49 Meeting abstract

22 Insufficient data

22 Foreign language paper

13 All or some participants were under 18 years old

11 Duplicates data from another (included) study

10 Modified version of PCS used

9 Not a study (e.g. correction to a publication; figure; protocol only)

64

6 No baseline

5 Not peer reviewed

4 Single case study

3 Misuse of PCS (for example changes to instructions)

2 Literature/systematic review

1 Paper not retrieved

Data cleaning 1 Double counting of data (paper reporting data duplicating that of another paper)

1 Implausible data (contains data above or below possible scores)

1 Data double-counted

Meta-analysis of the psychometric properties of the Pain ...

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